眼底病灶识别的仿真研究

Researchon Fundus Lesion Identification Simulation

研究眼底病灶识别的仿真问题。针对传统方法具有人为因素影响较大、主观性和烦琐性等缺陷,导致了眼底病灶识别度低、准确度低。为解决上述问题,提出一种改进的FCM算法分割眼底病灶,该算法对眼底病灶图像进行聚类分割,再通过数学形态学运算去除噪声。实验结果表明,该算法能有效地识别出眼底图像中的病灶。

Research on fundus lesion identification simulation.The traditional method is subjective and cumbersome and greatly influenced by human factors,which makes Fundus lesion identification lack of recognition degree and accuracy.To solve this problem,an improved FCM algorithm is used for segmentation of Fundus lesion,the algorithm clusters segmentation on the image of Fundus lesion,and then remove the noise by mathematical morphology operations.Experimental results show that the algorithm can effectively identify the lesion in the Fundus image.